Abstract
AbstractDoppler lidars are frequently used for wind measurements in the atmospheric boundary layer, but their data are subject to spatial averaging due to the pulse length of the laser and sampling frequency of the return signal. This spatial averaging also affects estimates of turbulence statistics like the velocity variance and outer scale of turbulence from Doppler lidar data. In this study a procedure from Frehlich and Cornman based on a von Kármán turbulence model was systematically applied to correct these effects of spatial averaging on turbulence statistics. The model was able to reduce the occurring bias of the velocity variance and outer scale of turbulence in a comparison of time series from a Doppler lidar and an ultrasonic anemometer. The measurements show that the bias of the velocity variance was reduced by 29% and that of the outer scale of turbulence by 43%. But both turbulence parameters had a remaining systematic error that could not be explained by the von Kármán model of the structure function.
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